“The whole is more than the sum of its parts” – Aristotle
“The ideal method of science is the study of the direct influence of one condition on another in experiments in which all other possible causes of variation are eliminated. Unfortunately, causes of variation often seem to be beyond control. In the biological sciences, especially, one often has to deal with a group of characteristics or conditions which are correlated because of a complex of interacting uncontrollable, and often obscure causes.” – Sewall Wright (1921)(pg 557)
For centuries scientific research has been concerned with breaking down the whole into its smallest and most simple parts. Aristotle’s proverb was considered more philosophy than science (Von Bertalanffy 1972). However, as Sewall Wright, one of the fathers of modern genetics, wrote nearly ninety years ago in the passage above – it can be very challenging to examine the behavior of isolated parts and, as he recognized in genetics research, outcomes can be the result of very, very, complex interactions that are not easily explained through isolated observation. This is true not only in science, but also in education, and sports. In this blog, I will discuss these opposite ends of the spectrum of analysis: first, a reductionist, bottom-up method and next, a holistic, top-down method (often referred to as systems thinking).
A reductionist method is concerned with the scientific attempt “to resolve or reduce complex phenomena into elementary parts and processes (Von Bertalanffy 1972)(pg 409).” From this approach, every scientific domain tries “to be as theoretically simplistic as possible (Sameroff 2010)(pg 07),” and is studied in isolation to observe cause and effect relationships.
Of importance to education and sports, the act of learning, from a reductionist perspective, is recognized as a cause-effect relationship through which specific practice (study of a school subject or practicing an axel) leads to the acquisition and retention of new knowledge or motor skills (Schmidt and Lee 2005, Koopmans 2014). In other words, specific practice is the cause and the acquisition of new knowledge or skills is the effect.
Traditional education functions on reductionist principles: you go to one class and study the subject in isolation with one teacher, then the bell rings and you walk to your next class to study the next subject. In this way, one’s overall education is compartmentalized into separate unrelated subjects and it is up to students to link those subjects together at some point later on (Forrester 1992). Similarly, many children participate in different sports and, since those sports are with different coaches and part of different organizations, general athletic development can also be compartmentalized or reductionist in nature. To go even deeper, it is common for many figure skaters to have a handful of different coaches. There might be a head coach, a jump coach, a choreographer, and a step and edge coach. In such a scenario, skaters put on a different hat, so-to-speak, for each coach to learn their skills in isolation from one another.
The reductionist belief is that, to better understand the whole, you break it down to learn how the individual parts work. Then when you know how the individual parts work, you must put them back together in bottom-up progression.
“Almost all understandable experiences reinforce the belief that causes are closely and obviously related to consequences. But in more complex systems, the cause of a difficulty is usually far distant in both time and space. The cause originated much earlier and arose from a different part of the system from where the symptoms appear.” – (Forrester 1992)(pg 07)
Systems thinking, is interested in the complex and dynamic relationships between all the parts that make up the whole and recognizes that the whole (the system of concern) is more (or at the very least different) than the sum of its parts. And in many cases, those individual parts will behave quite differently when they are part of the whole. What exactly is a system? A sports league is a system composed of teams. A team is a system composed of athletes. An athlete is a system composed of biological systems and subsystems. A school is a system composed of teachers and students who are in turn their own systems and so on.
An Important consideration from systems thinking is that many complex relationships exist between all the individual parts of the whole and that perhaps causality is more interconnected, circular, or mutual (Anderson and Johnson 1997). Accordingly, our behaviors are not necessarily the result of a linear chain of events but rather the result of complex interactions between many events from the past and present. By changing our viewpoint in such a way, we are less likely to misinterpret mere symptoms as actual root causes of behavior because if we step back and take in the whole picture, we may find that root causes are multifactorial, hidden deep beneath those obvious symptoms, and may have manifested in the distant past.
The act of learning from a systems perspective is one that is entirely nonlinear in nature (Koopmans 2014, Chow, Davids et al. 2015). From this perspective, learners are expected to progress through both rapid and slow periods of development; other periods that appear to regress, and yet others that seemingly remain stagnant for different durations. Small changes can lead to big effects and big changes can lead to small effects (Kelso 1995). Accordingly, the acquisition of knowledge in school or new motor skills in sport is not easily explained in a simple cause and effect manner as in, if one practices this exercise, one will acquire that skill. This approach reflects the understanding that different learning modalities (e.g. an exercise used to learn an axel) will be seemingly effective at times and ineffective at others and that the effects of each modality are context dependent.
If we look at the common scenario in education and figure skating where learning is compartmentalized between different subjects or coaches, we can see the pitfalls of failing to recognize the bigger picture when learning is considered a whole. According to (Forrester 1992):
“Education is compartmentalized into separate subjects that, in the real world, interact with one another. Social studies, physical science, biology, and other subjects are taught as if they were inherently different from one another, even though behavior in each rests on the same underlying concepts. For example, the dynamic structure that causes a pendulum to swing is the same as the core structure that causes employment and inventories to fluctuate in a product- distribution system and in economic business cycles. Humanities are taught without relating the dynamic sweep of history to similar behaviors on a shorter time scale that a student can experience in a week or a year (pg. 05-06).”
Forrester’s words reflect the same exact predicament of learning motor skills in compartmentalized fashion from different coaches. Steps and edges, jumps, and spins are all taught as if they were inherently different skills even though the actions of each should rest on the same underlying concepts. In some cases, students learn the same skills in different ways from different coaches, which compartmentalizes learning even further. For example, the way one learns a three turn should reflect the core technique of how one learns to spin and jump. The only way to “survive” such a predicament is to ignore what is being taught which could be why so many skaters who train in such away fail to remember what their coaches teach them from day to day. It is a survival mechanism.
Science is embracing such a multidisciplinary approach (Jablonka, Lamb et al. 2014), which focuses on relationships rather than isolation. Some argue that this multidisciplinary approach is the road to discovering lasting solutions, especially to health care problems (Disis and Slattery 2010). This shifting of methods in science reflects, in part, the need for student centered learning, which allows students to learn their subjects as if they were all part of a cohesive whole and reflects the influence of technology on businesses in the 21stcentury (Hannafin and Land 1997, Nair 2014).
Systems thinking provides the scaffolding for our Athlete Centered approach to teaching figure skating. In our view, motor skill acquisition and performance in figure skating isn’t as simple as the linear learning progression I described earlier. It is also about the dynamic relationships between skaters’ emotions; motivations; goals; other activities- especially academics; fatigue; growth and biological development; parents, other family members, and friends; skaters and other coaches at the rink; experiences from the past that shaped their current state; and so on. As coaches, we understand that each of those factors (and many more) contribute to the unique drives, dreams, and pursuits of each student. We also realize there is absolutely no magic formula to create champions and there is no single, causal, linear way to achieve success.
Ahmetov, I. I. and O. N. Fedotovskaya (2012). “Sports genomics: Current state of knowledge and future directions.” Cellular and molecular exercise physiology1(1): e1.
Anderson, V. and L. Johnson (1997). Systems thinking basics, Pegasus Communications Cambridge, MA.
Chow, J. Y., K. Davids, C. Button and I. Renshaw (2015). Nonlinear pedagogy in skill acquisition: An introduction, Routledge.
Disis, M. L. and J. T. Slattery (2010). “The road we must take: multidisciplinary team science.” Science translational medicine2(22): 22cm29-22cm29.
Druzhevskaya, A. M., I. I. Ahmetov, I. V. Astratenkova and V. A. Rogozkin (2008). “Association of the ACTN3 R577X polymorphism with power athlete status in Russians.” European journal of applied physiology103(6): 631-634.
Edelman, G. M. (1987). Neural Darwinism: The theory of neuronal group selection, Basic Books.
Forrester, J. W. (1992). “System dynamics and learner-centered-learning in kindergarten through 12th grade education.” Text of remarks delivered December12: 1992.
Hannafin, M. J. and S. M. Land (1997). “The foundations and assumptions of technology-enhanced student-centered learning environments.” Instructional science25(3): 167-202.
Issurin, V. B. (2013). “Training transfer: scientific background and insights for practical application.” Sports Medicine43(8): 675-694.
Jablonka, E., M. J. Lamb and A. Zeligowski (2014). Evolution in four dimensions, revised edition: Genetic, epigenetic, behavioral, and symbolic variation in the history of life, MIT press.
Kelso, J. (1995). Dynamic patterns: The self-organization of brain and behavior, Cambridge, MA: MIT Press.
Koopmans, M. (2014). “Nonlinear change and the black box problem in educational research.” Nonlinear dynamics, psychology, and life sciences18(1): 5-22.
Nair, P. (2014). Blueprint for Tomorrow: Redesigning Schools for Student-Centered Learning, ERIC.
Sameroff, A. (2010). “A unified theory of development: A dialectic integration of nature and nurture.” Child development81(1): 6-22.
Schmidt, R. A. and T. D. Lee (2005). “Motor control and learning: A behavioral emphasis.”
Schöner, G. and J. Spencer (2015). Dynamic thinking: A primer on dynamic field theory, Oxford University Press.
Von Bertalanffy, L. (1972). “The history and status of general systems theory.” Academy of Management Journal15(4): 407-426.
Wright, S. (1921). “Correlation and causation.” Journal of agricultural research20(7): 557-585.
For example, a reductionist approach to psychology is that one’s behaviors can be reduced to a series of stimulus-response (cause-and-effect) chains where an event triggers a response which may be the cause of yet another response and so on. Another example is the geneticist who reduces DNA to observe associations between specific genetic markers and behaviors such as this study (Druzhevskaya, Ahmetov et al. 2008)that compared different variants of a gene and athletic performance (power performance versus endurance performance). Yet another example of reductionism is the neurologist who reduces the complexity of the human brain to study the behavior of individual brain cells (neurons).